Leveraging Data Science for Global Health
Contributors: Majumder, Maimuna S.; Ordóñez, Patricia; Osorio, Juan Sebastian; Paik, Kenneth E.; Somai, Melek; Celi, Leo Anthony; Majumder, Maimuna S.; Ordóñez, Patricia; Osorio, Juan Sebastian; Paik, Kenneth E.; Somai, Melek
Publisher: Springer Nature
Published: 2020
Number of pages: 475
ISBN-13: 9783030479947
Subjects: Health & safety aspects of IT; Health economics; Medical equipment & techniques
Description: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Notes: Open Access Unrestricted online access

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